openWAR: An open source system for evaluating overall player performance in major league baseball

Baumer Benjamin S. (), Jensen Shane T. and Matthews Gregory J.
Additional contact information
Baumer Benjamin S.: Smith College – Statistical and Data Sciences, Northampton, MA, USA
Jensen Shane T.: Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
Matthews Gregory J.: Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA

Journal of Quantitative Analysis in Sports, 2015, vol. 11, issue 2, 69-84

Abstract: Within sports analytics, there is substantial interest in comprehensive statistics intended to capture overall player performance. In baseball, one such measure is wins above replacement (WAR), which aggregates the contributions of a player in each facet of the game: hitting, pitching, baserunning, and fielding. However, current versions of WAR depend upon proprietary data, ad hoc methodology, and opaque calculations. We propose a competitive aggregate measure, openWAR, that is based on public data, a methodology with greater rigor and transparency, and a principled standard for the nebulous concept of a “replacement” player. Finally, we use simulation-based techniques to provide interval estimates for our openWAR measure that are easily portable to other domains.

Keywords: baseball; R; reproducibility; simulation; statistical modeling (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://doi.org/10.1515/jqas-2014-0098 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jqsprt:v:11:y:2015:i:2:p:69-84:n:4

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jqas/html

DOI: 10.1515/jqas-2014-0098

Access Statistics for this article

Journal of Quantitative Analysis in Sports is currently edited by Mark Glickman

More articles in Journal of Quantitative Analysis in Sports from De Gruyter
Bibliographic data for series maintained by Peter Golla ().